Large Language Models (LLMs) like Claude and GitHub Copilot are revolutionizing how developers write code. However, they face a critical limitation: they’re trained on data with knowledge cutoffs, meaning they lack information about: Latest SDK versions and their breaking changes Actual working code examples from official repositories Platform-specific implementations (Android...

In the world of AI-assisted development, one of the most common frustrations is receiving code based on outdated documentation. AI models are typically trained on static datasets, meaning their knowledge can be months or even years behind. This often leads to suggestions that use deprecated functions, hallucinated APIs, or code...